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Integrator complex subunit 12 knockout overcomes a transcriptional block to HIV latency reversal [AutoCUT&Tag]

GSE277305 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 44 samples Submitted 2024/09/17 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 44 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
44 samples: 12 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
The latent HIV reservoir is a major barrier to HIV cure. Combining latency reversal agents (LRAs) with differing mechanisms of action such as AZD5582, a non-canonical NF-kB activator, and I-BET151, a bromodomain inhibitor are appealing towards inducing HIV reactivation. However, even this LRA combination needs improvement as it is inefficient at activating proviruses in cells from people living with HIV (PLWH).
Read the full summary ↓
We performed a CRISPR screen in conjunction with AZD5582 & I-BET151 and identified a member of the Integrator complex as a target to improve this LRA combination, specifically Integrator complex subunit 12 (INTS12). Integrator functions as a genome-wide attenuator of transcription that acts on elongation through its RNA cleavage and phosphatase modules. Knockout of INTS12 in both cell line models and in CD4 T cells from virally suppressed PLWH improves reactivation at the transcriptional level and is more specific than AZD5582 & I-BET151 treatment alone. INTS12 is present on chromatin at the promoter of HIV and therefore its effect on HIV may be direct. Additionally, we observe more RNAPII in the gene body of HIV only with the combination of INTS12 knockout with AZD5582 & I-BET151 indicating the combination may specifically overcome an elongation block to reactivation. We also observe viral RNA in the supernatant from CD4 T cells of all three virally suppressed PLWH tested upon INTS12 knockout suggesting that INTS12 controls full-length HIV RNA and virus production ex vivo.
This dataset
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Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE277305_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1161694 and SRA study SRP532960. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
J-Lat 10.6_WT_AZD5582andIBET-151_INTS12_1 ×5 J-Lat 10.6_WT_AZD5582andIBET-151_INTS12_2 ×5 J-Lat 10.6_INTS12KO_AZD5582andIBET-151_INTS12… ×4 J-Lat 10.6_INTS12KO_DMSO_INTS12_1 ×4 J-Lat 10.6_INTS12KO_DMSO_INTS12_2 ×4 J-Lat 10.6_WT_DMSO_INTS12_1 ×4 J-Lat 10.6_INTS12KO_AZD5582andIBET-151_INTS12… ×3 J-Lat 10.6_INTS12KO_AZD5582andIBET-151_RPB3 ×3 +4 more

Supports a between-group comparison across 44 samples.

How we read this: 12 replicated groups read from 44 sample titles; they account for 44 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 4 more — browse all 44 samples with per-sample file links →

Datasets on a similar topic

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